• Title/Summary/Keyword: 건강보험심사청구

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An Study on Decision Tree Analysis with Imbalanced Data Set : A Case of Health Insurance Bill Audit in General Hospital (의사결정나무 분석에서 불균형 자료의 분석 연구 : 종합병원의 건강보험료 청구 심사 사례)

  • Heo Jun;Kim Jong-U
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.1667-1676
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    • 2006
  • 다른 산업과 달리 병원/의료 산업에서는 건강 보험료 심사 평가라는 독특한 검증 과정이 필수적으로 있게 된다. 건강 보험료 심사 평가는 병원의 수익 문제 뿐 아니라 적정한 진료행위를 하는 병원이라는 이미지와도 맞물려 매우 중요한 분야이며, 특히 대형 종합병원일수록 이 부분에 많은 심사관련 인력들을 투입하여, 병원의 수익과 명예를 위해서 업무를 수행하고 있다. 본 논문은 이러한 건강보험료 청구 심사 과정에서, 사전에 수많은 진료 청구 건 중 심사 평가에서 삭감이 될 수 있는 진료 청구 건을 데이터 마이닝을 통해서 발견하여, 사전의 대비를 철저히 하고자 하는 한 국내의 대형 종합병원의 사례를 소개하고자 한다. 데이터 마이닝을 적용함에 있어, 주요한 문제점 중의 하나는 바로 지도학습 기법을 적용하기에 곤란한 데이터 불균형 문제가 발생하는 것이다. 이런 불균형 문제를 해소하고, 비교 조건 중에 가장 효율적인 삭감 예상 진료 건 탐지 모형을 만들어 내기 위하여 데이터 불균형 문제의 기본 해법인 과, Sampling 오분류 비용의 다양하고 혼합적인 적용을 통하여, 적합한 조건을 가지는 의사결정 나무 모형을 도출하였다.

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Dentists' Opinions in The Dental Field of Present Health Insurance Claim and Review (건강보험중 구강요양급여의 청구 및 심사에 관한 치과의사의 견해)

  • Chang, Yong-Seog;Ahn, Yong-Woo;Park, June-Sang;Ko, Myung-Yun
    • Journal of Oral Medicine and Pain
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    • v.30 no.2
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    • pp.215-230
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    • 2005
  • The study was intended to investigate how dentists in private dental clinic thought on the present claim and review of dental insurance to reflect it in future establishing dental insurance policies. 1,465 dentists who were running own dental clinic in Pusan Metropolitan City and the south part of Kyungsang province were surveyed in February, 2004. A total of 406 copies of finished questionnaire were finally retrieved and analyzed. The findings are as follows. 1. About insurance claim affairs : Most of the subject of insurance claim was by dentist himself or dental hygienist(nurse). Agency claiming was carried under 20% of total insurance claim. 2. The degree of attendance on insurance lecture : The degree of attendance on insurance lecture was relatively low. 3. Filing a protest against insurance claim : Filing a protest against insurance claim was reavealed about half-and-half for "have been" or "have not been". 4. Private clinic dentist,s opinion about the regulations affecting review of dental insurance : Private clinic dentists opinion about current guide for insurance review of dental fee was“the guidance is difficult and unfair cutback of claim fee may be carried”. 5. The affairs about health insurance review agency : About 70% of private clinic dentists have dissatisfaction on health insurance review agency. 6. Standpoint of private clinic dentists about issuance of receipt for dental fee : About 70% of private clinic dentist have an difficulty in issuance of receipt for dental fee. 7. The affairs about change insurance noncoverage treatment to insurance coverage treatment : Most of private clinic dentists hoped that insurance coverage about full mouth scaling, pit and fissure sealant, fluoride application. But they do not hoped that insurance coverage about geriatric denture, prothodontic treatment except precious metal, photopolymerization resin treatment.

Decision Tree Induction with Imbalanced Data Set: A Case of Health Insurance Bill Audit in a General Hospital (불균형 데이터 집합에서의 의사결정나무 추론: 종합 병원의 건강 보험료 청구 심사 사례)

  • Hur, Joon;Kim, Jong-Woo
    • Information Systems Review
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    • v.9 no.1
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    • pp.45-65
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    • 2007
  • In medical industry, health insurance bill audit is unique and essential process in general hospitals. The health insurance bill audit process is very important because not only for hospital's profit but also hospital's reputation. Particularly, at the large general hospitals many related workers including analysts, nurses, and etc. have engaged in the health insurance bill audit process. This paper introduces a case of health insurance bill audit for finding reducible health insurance bill cases using decision tree induction techniques at a large general hospital in Korea. When supervised learning methods had been tried to be applied, one of major problems was data imbalance problem in the health insurance bill audit data. In other words, there were many normal(passing) cases and relatively small number of reduction cases in a bill audit dataset. To resolve the problem, in this study, well-known methods for imbalanced data sets including over sampling of rare cases, under sampling of major cases, and adjusting the misclassification cost are combined in several ways to find appropriate decision trees that satisfy required conditions in health insurance bill audit situation.

The Job Stress and Mental Health of the Insurance Reviewer (보험심사 근무직의 직무스트레스와 정신건강)

  • Kyoungjin Song;Jeongwon Lee
    • Journal of Service Research and Studies
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    • v.11 no.1
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    • pp.31-44
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    • 2021
  • The net function of the domestic medical insurance system is highly regarded, but due to the problem of incomplete coverage, the public wants to secure coverage through private medical insurance subscription. As a result, the subscription rate of private medical insurance has recently increased, and the billing rate has also increased. As the number of people seeking private medical insurance increased, workers at private medical insurance companies are experiencing increased job stress and side effects, especially for insurance reviewers who are in charge of paying insurance, such as communicating with customers who claimed insurance and contributing to the company's profit. In response, this study analyzed the effects of job stress on mental health of insurance reviewers and conducted a descriptive survey study to reduce job stress of insurance reviewers and promote mental health. The analysis shows that job stress for insurance reviewers has a significant impact on mental health (+). In detail, job stress has a significant impact on all four factors: social performance and self-confidence, depression, sleeping disturbance and anxiety, and general well-being and vitality. This study showed that job stress in insurance reviewers has a significant (+) impact on mental health. Job stress can cause side effects in organizational aspects, such as reducing enthusiasm for job performance and increasing turnover and resignation rates, but it can also worsen individual physical health and cause diseases such as depression and anxiety, causing mental health to be impoverished. Therefore, in order to prevent this, appropriate work stress prevention methods and countermeasures should be provided to help reduce work stress and improve mental health.

Development of Advanced TB Case Classification Model Using NHI Claims Data (국민건강보험 청구자료 기반의 결핵환자 분류 고도화 모형 개발)

  • Park, Il-Su;Kim, Yoo-Mi;Choi, Youn-Hee;Kim, Sung-Soo;Kim, Eun-Ju;Won, Si-Yeon;Kang, Sung-Hong
    • Journal of Digital Convergence
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    • v.11 no.9
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    • pp.289-299
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    • 2013
  • The aim of this study was to enhance the NHI claims data-based tuberculosis classification rule of KCDC(Korea centers for disease control & prevention) for an effective TB surveillance system. 8,118 cases, 10% samples of 81,199 TB cases from NHI claims data during 2009, were subject to the Medical Record Survey about whether they are real TB patients. The final study population was 7,132 cases whose medical records were surveyed. The decision tree model was evaluated as the most superior TB patients detection model. This model required the main independent variables of age, the number of anti-tuberculosis drugs, types of medical institution, tuberculosis tests, prescription days, types of TB. This model had sensitivity of 90.6%, PPV of 96.1%, and correct classification rate of 93.8%, which was better than KCDC's TB detection model with two or more NHI claims for TB and TB drugs(sensitivity of 82.6%, PPV of 95%, and correct classification rate of 80%).

A Study on the Development and Implementation of a Data-mining Based Prototype for Hospital Bill Claim Reduction System (데이터마이닝 기법을 활용한 의료보험 진료비청구 삭감분석시스템 개발 및 구현에 관한 연구)

  • Yoo, Sang-Jin;Park, Mun-Ro
    • Information Systems Review
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    • v.7 no.1
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    • pp.275-295
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    • 2005
  • Changes in business environment caused by globalization of the world economy and the beginning of the knowledge society forced hospitals to equip with tools for the enhanced competitiveness. In other words, hospitals must aim three targets such as acquisition of advanced medical skills and equipments, improvement of service level for patients, and achievement of superior managerial performance simultaneously. This study has been done to suggest a way to reduce the possibility of hospital bill claim reduction as an alternative for the achievement of superior managerial performance. If the reduction rate of hospital bill claim is high, it will put negative impact on the hospital's revenue stream and hospital's reliability. Thus, if they want to stay competitive, hospitals need to device ways to cut the reduction rate as much as possible. In this study, a prototype system has been developed and implemented to check the possibility to cut the reduction rate through deep analysis of causes of reduction. The prototype first developed utilizing data mining techniques and the relation rules algorithm. Then the prototype was tested its performance using the D hospital's live data.

치과병원 증가, 양질 진료 서비스냐, 과다 진료비 청구냐

  • The Korean Dental Association
    • The Journal of the Korean dental association
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    • v.38 no.10 s.377
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    • pp.935-941
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    • 2000
  • 건강보험심사평가원이 파악한 전국의 치과병원 개수는 48개(대학의 치과병원, 국공립 치과병원 제외) 이중 올해 새로 개설신고한 치과병원이 16개에 이른다. 치과병원의 증가로 치과의사의 활로 개척 및 수련기회의 증가, 연계된 진료 및 질 높은 진료 가능 등 긍정적 측면도 있으나 과다한 시설투자로 인한 지나친 요금 청구, 주변 개원의와의 마찰, 과대광고의 가능성 등 문제점도 제기되고 있다. 이에 치과병원의 현황을 살펴보고 치과병원의 긍정적인 측면과 부정적인 측면 등을 살펴보도록 한다.

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The Prediction of Survival of Breast Cancer Patients Based on Machine Learning Using Health Insurance Claim Data (건강보험 청구 데이터를 활용한 머신러닝 기반유방암 환자의 생존 여부 예측)

  • Doeggyu Lee;Kyungkeun Byun;Hyungdong Lee;Sunhee Shin
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.2
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    • pp.1-9
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    • 2023
  • Research using AI and big data is also being actively conducted in the health and medical fields such as disease diagnosis and treatment. Most of the existing research data used cohort data from research institutes or some patient data. In this paper, the difference in the prediction rate of survival and the factors affecting survival between breast cancer patients in their 40~50s and other age groups was revealed using health insurance review claim data held by the HIRA. As a result, the accuracy of predicting patients' survival was 0.93 on average in their 40~50s, higher than 0.86 in their 60~80s. In terms of that factor, the number of treatments was high for those in their 40~50s, and age was high for those in their 60~80s. Performance comparison with previous studies, the average precision was 0.90, which was higher than 0.81 of the existing paper. As a result of performance comparison by applied algorithm, the overall average precision of Decision Tree, Random Forest, and Gradient Boosting was 0.90, and the recall was 1.0, and the precision of multi-layer perceptrons was 0.89, and the recall was 1.0. I hope that more research will be conducted using machine learning automation(Auto ML) tools for non-professionals to enhance the use of the value for health insurance review claim data held by the HIRA.

Analysis of Outpatient Claim Trends and Utilization According to Health Coverage for Chuna Manual Therapy (추나 요법 건강보험 급여화에 따른 외래 청구 현황 및 의료이용 분석)

  • JaeYong Dong;JinHan Ju;SangHeon Yoon
    • Korea Journal of Hospital Management
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    • v.28 no.3
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    • pp.47-57
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    • 2023
  • Purpose: Health expenditure and utilization of Korean medicine are increasing every year. Since Chuna Manual Therapy was covered by National Health Insurance in 2019, it is predicted that the usage of Chuna Manual Therapy would be also increasing. However, there are few studies about Chuna Manual Therapy using Korean National Health Insurance claims database. Therefore, we will investigate the utilization trend of outpatient's Chuna Manual Therapy using Korean National Health Insurance database and suggest political implications. Methodology: The Korean National Health Insurance claims database was used to identify outpatient's Chuna Manual Therapy usage spanning 4 years from 2019-2023 and the number of Chuna Manual Therapy claims were approximately 18.61 million. Findings: The number of Chuna Manual Therapy claims and patients, health expenditure of Chuna Manual Therapy have been increasing spanning 4 years among over 65 aged. In the case of female patients, the number of Chuna Manual Therapy claims was more than male patients and health spending related to Chuna Manual Therapy was also higher than male patients. Most patients visited Korean medicine clinics due to musculoskeletal diseases, and most claims were from rural regions. Practical Implication: Since Chuna Manual Therapy was covered by National Health Insurance in 2019, Utilization of Chuna Manual Therapy has been increased overall. In particular, Chuna Manual Therapy is mostly implemented in the elderly, Korean medicine clinics, and local areas, thus policy managers will need to consider this.

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